Hybrid fuzzy multi-objective particle swarm optimization for taxonomy extraction

Ontology learning refers to an automatic extraction of ontology to produce the ontology learning layer cake which consists of five kinds of output: terms, concepts, taxonomy relations, non-taxonomy relations and axioms. Term extraction is a prerequisite for all aspects of ontology learning. It is the automatic mining of complete terms from the input document. Another important part of ontology is taxonomy, or the hierarchy of concepts. It presents a tree view of the ontology and shows the inheritance between subconcepts and superconcepts. In this research, two methods were proposed for improving the performance of the extraction result. The first method uses particle swarm optimization in order to optimize the weights of features. The advantage of particle swarm optimization is that it can calculate and adjust the weight of each feature according to the appropriate value, and here it is used to improve the performance of term and taxonomy extraction. The second method uses a hybrid technique that uses multi-objective particle swarm optimization and fuzzy systems that ensures that the membership functions and fuzzy system rule sets are optimized. The advantage of using a fuzzy system is that the imprecise and uncertain values of feature weights can be tolerated during the extraction process. This method is used to improve the performance of taxonomy extraction. In the term extraction experiment, five extracted features were used for each term from the document. These features were represented by feature vectors consisting of domain relevance, domain consensus, term cohesion, first occurrence and length of noun phrase. For taxonomy extraction, matching Hearst lexico-syntactic patterns in documents and the web, and hypernym information form WordNet were used as the features that represent each pair of terms from the texts. These two proposed methods are evaluated using a dataset that contains documents about tourism. For term extraction, the proposed method is compared with benchmark algorithms such as Term Frequency Inverse Document Frequency, Weirdness, Glossary Extraction and Term Extractor, using the precision performance evaluation measurement. For taxonomy extraction, the proposed methods are compared with benchmark methods of Feature-based and weighting by Support Vector Machine using the f-measure, precision and recall performance evaluation measurements. For the first method, the experiment results concluded that implementing particle swarm optimization in order to optimize the feature weights in terms and taxonomy extraction leads to improved accuracy of extraction result compared to the benchmark algorithms. For the second method, the results concluded that the hybrid technique that uses multi-objective particle swarm optimization and fuzzy systems leads to improved performance of taxonomy extraction results when compared to the benchmark methods, while adjusting the fuzzy membership function and keeping the number of fuzzy rules to a minimum number with a high degree of accuracy

TOTh 2011 Proceedings - Terminology & Ontology: Theories and applications

International audienceAvant-proposLa Terminologie est un domaine scientifique par nature pluridisciplinaire. Elle puise, entre autres, à la linguistique, la théorie de la connaissance, la logique. Pour que cette diversité soit une richesse, il faut lui offrir un cadre approprié au sein duquel elle puisse s’exprimer et s’épanouir : c’est une des raisons d’être des Conférences TOTh. Dans ce contexte, la formation et la transmission des connaissances jouent un rôle essentiel. La Formation TOTh, programmée sur un jour et demi précédant la conférence, se déroule depuis 2011 sur deux années consécutives dédiées pour l’une à la dimension linguistique et pour l’autre à la dimension conceptuelle de la terminologie, deux dimensions intimement liées. La Disputatio, introduite à partir de cette année, renoue avec une forme d’enseignement et de recherche héritée de la scolastique. Elle vise, à travers une lecture commentée effectuée par un membre du comité scientifique, à donner accès à des textes jugés fondateurs de notre domaine, trop souvent oubliés voire ignorés.La cinquième édition des Conférences TOTh a également été l’occasion de mettre en place un Prix « Jeune chercheur ». Décerné par le comité scientifique lors de la conférence, il récompense le travail soumis à TOTh d’un de nos jeunes collègues. Notre collègue Michele Prandi, professeur à l’Università degli Studi di Genova, a ouvert la Conférence TOTh 2011 par un exposé passionnant sur : « Signes, signifiés, concepts : pour un tournant philosophique en linguistique ». Le ton était donné.Ont suivi douze communications (hors conférence d’ouverture et disputatio) réparties sur deux jours en six sessions animées par différents présidents. Elles ont permis d’aborder en profondeur – chaque intervention dure au minimum 45 minutes – de nombreux sujets tant théoriques que pratiques rappelant qu’il ne peut y avoir de terminologie sans langue de spécialité ni savoir spécialisé.Les douze communications, équitablement réparties sur les deux langues officielles de la conférence et provenant de sept pays différents, confirment l’audience internationale acquise aujourd’hui par TOTh.Avant de vous souhaiter bonne lecture de ces actes, j’aimerais terminer en remerciant tous les participants de TOTh 2011 pour la richesse des débats et des moments partagés. Christophe RochePrésident du comité scientifiqu

Ontologies for Legal Relevance and Consumer Complaints. A Case Study in the Air Transport Passenger Domain

Applying relevant legal information to settle complaints and disputes is a common challenge for all legal practitioners and laymen. However, the analysis of the concept of relevance itself has thus far attracted only sporadic attention. This thesis bridges this gap by understanding the components of complaints, and by defining relevant legal information, and makes use of computational ontologies and design patterns to represent this relevant knowledge in an explicit and structured way. This work uses as a case-study a real situation of consumer disputes in the Air Transport Passenger domain. Two artifacts were built: the Relevant Legal Information in Consumer Disputes Ontology, and its specialization, the Air Transport Passenger Incidents Ontology, aimed at modelling relevant legal information; and the Complaint Design Pattern proposed to conceptualize complaints. In order to demonstrate the ability of the ontologies to serve as a knowledge base for a computer program providing relevant legal information, a demonstrative application was developed

Approaches to legal ontologies : theories, domains, methodologies

Legal ontologies have proved crucial for representing, processing and retrieving legal information, and will acquire an increasing significance in the emerging framework of the Semantic Web. Despite the many research projects in the field, a collective reflection on the theoretical foundations of legal ontology engineering was still missing. This book bridges the gap, by exploring current methodologies and theoretical approaches to legal ontologies. It gathers 16 papers, each of them presenting issues and solutions for ontology engineering related to a particular approach to, or aspect of, the law: comparative law, case-based reasoning, multilingualism, complex- systems, sociolegal analysis, legal theory, social ontology, ontology learning, computational ontology, service ontology, cognitive science, document modelling, large legal databases, scientific, linguistic and legal-technology perspectives. The book will thus interest researchers in legal informatics, artificial intelligence and law, legal theory, legal philosophy, legal sociology, comparative law, as well as developers of applications based on the intelligent management of legal information, in both e-commerce and e-government (e-administration, e-justice, e-democracy).Foreword; Pompeu Casanovas, Giovanni Sartor.- Preface; Barry Smith.- 1 Introduction. Theory and Methodology in Legal Ontology Engi-neering: Experiences and Future Directions; Pompeu Casanovas, Giovanni Sartor, Maria Angela Biasiotti, Meritxell Fernández-Barrera.- 2 The Legal Theory Perspective: Doctrinal Conceptual Systems vs. Computational Ontologies; Meritxell Fernández-Barrera, Giovanni Sartor.- 3 Empirically Grounded Development of Legal Ontologies: a Socio-Legal Perspective; Pompeu Casanovas, Núria Casellas, Joan-Josep Vallbé.- 4 A Cognitive Science Perspective on Legal Ontologies; Joost Breuker, Rinke Hoekstra.- 5 Social Ontology and Documentality; Maurizio Ferraris.- 6 The Case-Based Reasoning Approach: Ontologies for Analogical Legal Argument; Kevin D. Ashley.- 7 A Complex-System Approach: Legal Knowledge, Ontology, In-formation and Networks; Pierre Mazzega, Danièle Bourcier, Paul Bourgine, Nadia Nadah, Romain Boulet.- 8 The Multi-layered Legal Information Perspective; Guido Boella, Piercarlo Rossi.- 9 Legal Ontologies: the Linguistic Perspective; Maria Angela Biasiotti, Daniela Tiscornia.- 10 A Legal Document Ontology: the Missing Layer in Legal Docu-ment Modelling; Monica Palmirani, Luca Cervone, Fabio Vitali.- 11 From Thesaurus towards Ontologies in Large Legal Databases; Ángel Sancho Ferrer, Carlos Fernández Hernández, José Manuel Mateo Rivero.- 12 The Computational Ontology Perspective: Design Patterns for Web Ontologies; Aldo Gangemi, Valentina Presutti, Eva Blomqvist.- 13 A Learning Approach for Knowledge Acquisition in the Legal Domain; Enrico Francesconi.- 14 Towards an Ontological Foundation for Services Science: the Legal Perspective; Roberta Ferrario, Nicola Guarino, Meritxell Fernández-Barrera.- 15 Legal Multimedia Ontologies and Semantic Annotation for Search and Retrieval; Jorge González-Conejero.- Index